Scope of Technical Committees

Info

(status August 2017)

Each one of the nine Coordinating Committees (CCs) consists of a number of Technical Committees (TCs). Each TC coincides with a technical area within the CC. The scope of each technical area is described below.

1.2 Adaptative and Learning Systems

Developing control design methods for all systems that are subject to model uncertainty and compensating for uncertainty by using adaptation and machine learning techniques. The TC members' expertise include the design of adaptive controllers, adaptive state observers, adaptive parameter estimators, adaptive predictors, adaptive filters, etc.

1.3 Discrete Event and Hybrid Systems

All aspects of analysis and control of Discrete Event Systems and Hybrid Systems.

1.4 Stochastic Systems

All aspects related to probabilistic and statistical methods in modelling, identification, estimation and control.

1.5 Networked Systems

Networked systems are complex dynamical systems composed of a large number of simple subsystems interacting through a communication medium. Control systems operating over (resource-constrained) communication networks and multi-agent systems are at the heart of this TC. Networked systems arise as natural models in many areas of engineering and sciences, such as autonomous unmanned vehicles, cooperative robotics, smart grids, biological networks, internet-of-things and many more.

2.3 Non-linear Control Systems

Methods for analysis and design of control systems described by non-linear differential or difference equations including the application of these methods.

2.4 Optimal Control

The development and application of theory and methods for solving optimal control problems, as well as the closed-loop implementation of optimal controllers on real-time computer systems. Particular methods include, but are not limited to, the calculus of variations, Pontryagin's maximum principle, dynamic programming, model predictive control and differential games.

2.5 Robust Control

Modelling of systems affected by uncertainty and the development of computational techniques for analysis, optimal controller synthesis and implementation.

2.6. Distributed Parameter Systems

3 COMPUTERS, COGNITION AND COMMUNICATION

3.1 Computers for Control

Embedded and cyber-physical systems for real- time control with special emphasis in model-driven paradigm, modeling languages, verification & validation and certification, execution platforms including multi-core, real-time operating systems, virtualization layer for mixed-criticality systems and networks. Scheduling methods and real-time networks, as well as control techniques for computer systems.

3.2 Computational Intelligence in Control

Focuses on all aspects of knowledge-based, fuzzy and neuro-fuzzy and neural (both, artificial and biologically plausible) systems and evolutionary algorithms relevant to control, both in theory and application driven.

3.3 Telematics: Control via Communication Networks

Computerized and telecommunication-based automation systems providing services to remote equipment for tele-operation, tele-maintenance, tele-medicine and tele-education, and their methodologies. Concepts of Cyber Physical Systems, Industrial Internet and of Internet of Thins, which enlarge the scope of classical remote control.

4 MECHATRONICS, ROBOTICS AND COMPONENTS

4.2 Mechatronics Systems

The synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and processes.

4.5 Human-Machine Systems

This TC is concerned with complex technical or social systems where human factors and tight human-machine interaction/coupling play a significant role as an integral component. It is primarily aimed at promoting analysis, design, modeling, optimization, control, and evaluation of human-machine systems, human-automation integration, and brain-machine interfacing systems.

5 MANUFACTURING SYSTEMS

5.1 Manufacturing Plant Control

All aspects of modelling, methodologies, tools, applications related to automation, information and communication technologies needed to control the manufacturing plant within the e-enterprise. Investigations on new manufacturing plants as advocated by "Factory of the Future" or "Industry 4.0" visions.

5.2 Manufacturing Modelling for Management and Control

Models of e-manufacturing and supply chain systems, for production and service management, design, and control in communication and Internet based enterprises.

8.2 Biological and Medical Systems

Applications of systems, modelling, informatics and control concepts, methodology and techniques in biology, physiology, medicine and healthcare.

8.3 Modelling and Control of Environmental Systems

Modelling and control methodologies for reliable management of natural resources and prevention and mitigation of environmental hazards and disasters. Application areas include, but are not limited to, urban and rural water systems and pollution control of soil, water, and air.

8.4 Biosystems and Bioprocesses

Promotion of research and development in all major areas of biotechnology where computers are used to aid bioprocess design, supervision, diagnosis, operation, optimisation and control.

9 SOCIAL SYSTEMS

9.1 Economic, Business and Financial Systems

Modeling, analysis, synthesis, control, and management of Economic, Business, and Financial Systems. Operating at the interface between economics, business administration and financial engineering. Exploring theoretical and computational methods and tools for decision and control in economics, finance and management.

9.2 Social Impact of Automation

Relations between automated systems and social environments, including social effects of automation, requirements for automation development, and environmental and health implications.

9.3 Control for Smart Cities

Promote research and education of control for smart cities, includes but is not limited to buildings, transportation systems, water system management, pollution monitoring and control systems.

9.4 Control Education

Education issues in control engineering. Methodologies for improving the theory, practice and accessibility of control systems education. Improving awareness of the general population in the importance of systems and control.

9.5 Technology, Culture and InternationalStability (TECIS)

Identification, definition, and improvement of factors which significantly influence international stability and improve its effectiveness.

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